When Amazon Web Services (AWS) launched Amazon Q Developer as a preview last year, it changed my experience of interacting with AWS services and, at the same time, maximizing the potential of AWS services on a daily basis. Trained on 17 years of AWS knowledge and experience, this generative artificial intelligence (generative AI)–powered assistant helps me build applications on AWS, research best practices, perform troubleshooting, and resolve errors.
Today, we are announcing the general availability of Amazon Q Developer. In this announcement, we have a few updates, including new capabilities. Let’s get started.
New: Amazon Q Developer has knowledge of your AWS account resources
This new capability helps you understand and manage your cloud infrastructure on AWS. With this capability, you can list and describe your AWS resources using natural language prompts, minimizing friction in navigating the AWS Management Console and compiling all information from documentation pages.
To get started, you can navigate to the AWS Management Console and select the Amazon Q Developer icon.
With this new capability, I can ask Amazon Q Developer to list all of my AWS resources. For example, if I ask Amazon Q Developer, “List all of my Lambda functions,” Amazon Q Developer returns the response with a set of my AWS Lambda functions as requested, as well as deep links so I can navigate to each resource easily.
Prompt for you to try: List all of my Lambda functions.
I can also list my resources residing in other AWS Regions without having to navigate through the AWS Management Console.
Prompt for you to try: List my Lambda functions in the Singapore Region.
Not only that, this capability can also generate AWS Command Line Interface (AWS CLI) commands so I can make changes immediately. Here, I ask Amazon Q Developer to change the timeout configuration for my Lambda function.
Prompt for you to try: Change the timeout for Lambda function <NAME of AWS LAMBDA FUNCTION> in the Singapore Region to 10 seconds.
I can see Amazon Q Developer generated an AWS CLI command for me to perform the action. Next, I can copy and paste the command into my terminal to perform the change.
$> aws lambda update-function-configuration --function-name <AWS_LAMBDA_FUNCTION_NAME> --region ap-southeast-1 --timeout 10
{
"FunctionName": "<AWS_LAMBDA_FUNCTION_NAME>",
"FunctionArn": "arn:aws:lambda:ap-southeast-1:<ACCOUNT_ID>:function:<AWS_LAMBDA_FUNCTION_NAME>",
"Runtime": "python3.8",
"Role": "arn:aws:iam::<ACCOUNT_ID>:role/service-role/-role-1o58f7qb",
"Handler": "lambda_function.lambda_handler",
"CodeSize": 399,
"Description": "",
"Timeout": 10,
...
<truncated for brevity> }What I really like about this capability is that it minimizes the time and effort needed to get my account information in the AWS Management Console and generate AWS CLI commands so I can immediately implement any changes that I need. This helps me focus on my workflow to manage my AWS resources.
Amazon Q Developer can now help you understand your costs (preview)
To fully maximize the value of cloud spend, I need to have a thorough understanding of my cloud costs. With this capability, I can get answers to AWS cost-related questions using natural language. This capability works by retrieving and analyzing cost data from AWS Cost Explorer.
Recently, I’ve been building a generative AI demo using Amazon SageMaker JumpStart, and this is the right timing because I need to know the total spend. So, I ask Amazon Q Developer the following prompt to know my spend in Q1 this year.
Prompt for you to try: What were the top three highest-cost services in Q1?
From the Amazon Q response, I can further investigate this result by selecting the Cost Explorer URL, which will bring me to the AWS Cost Explorer dashboard. Then, I can follow up with this prompt:
Prompt for you to try: List services in my account which have the most increment month over month. Provide details and analysis.
In short, this capability makes it easier for me to develop a deep understanding and get valuable insights into my cloud spending.
Amazon Q extension for IDEs
As part of the update, we also released an Amazon Q integrated development environment (IDE) extension for Visual Studio Code and JetBrains IDEs. Now, you will see two extensions in the IDE marketplaces: (1) Amazon Q and (2) AWS Toolkit.
If you’re a new user, after installing the Amazon Q extension, you will see a sign-in page in the IDE with two options: using AWS Builder ID or single sign-on. You can continue to use Amazon Q normally.
For existing users, you will need to update the AWS Toolkit extension in your IDEs. Once you’ve finished the update, if you have existing Amazon Q and Amazon CodeWhisperer connections, even if they’re expired, the new Amazon Q extension will be automatically installed for you.
If you’re using Visual Studio 2022, you can use Amazon Q Developer as part of the AWS Toolkit for Visual Studio 2022 extension.
Free access for advanced capabilities in IDE
As you might know, you can use AWS Builder ID to start using Amazon Q Developer in your preferred IDEs. Now, with this announcement, you have free access to two existing advanced capabilities of Amazon Q Developer in IDE, Amazon Q Developer Agent for software development and Amazon Q Developer Agent for code transformation. I’m really excited about this update!
With the Amazon Q Developer Agent for software development, Amazon Q Developer can help you develop code features for projects in your IDE. To get started, you enter /dev in the Amazon Q Developer chat panel. My colleague Séb shared with me the following screenshot when he was using this capability for his support case project. He used the following prompt to generate an implementation plan for creating a new API in AWS Lambda:
Prompt for you to try: Add an API to list all support cases. Expose this API as a new Lambda function
Amazon Q Developer then provides an initial plan and you can keep on iterating this plan until you’re sure mostly everything is covered. Then, you can accept the plan and select Insert code.
The other capability you can access using AWS Builder ID is Developer Agent for code transformation. This capability will help you in upgrading your Java applications in IntelliJ or Visual Studio Code. Danilo described this capability last year, and you can see his thorough journey in Upgrade your Java applications with Amazon Q Code Transformation (preview).
Improvements in Amazon Q Developer Agent for Code Transformation
The new transformation plan provides details specific to my applications to help me understand the overall upgrade process. To get started, I enter /transform in the Amazon Q Developer chat and provide the necessary details for Amazon Q to start upgrading my java project.
In the first step, Amazon Q identifies and provides details on the Java Development Kit (JDK) version, dependencies, and related code that needs to be updated. The dependencies upgrades now include upgrading popular frameworks to their latest major versions. For example, if you’re building with Spring Boot, it now gets upgraded to version 3 as part of the Java 17 upgrade.
In this step, if Amazon Q identifies any deprecated code that Java language specifications recommend replacing, it will make those updates automatically during the upgrade. This is a new enhancement to Amazon Q capabilities and is available now.
In the third step, this capability will build and run unit tests on the upgraded code, including fixing any issues to ensure the code compilation process will run smoothly after the upgrade.
With this capability, you can upgrade Java 8 and 11 applications that are built using Apache Maven to Java version 17. To get started with the Amazon Q Developer Agent for code transformation capability, you can read and follow the steps at Upgrade language versions with Amazon Q Code Transformation. We also have sample code for you to try this capability.
Things to know
- Availability — To learn more about the availability of Amazon Q Developer capabilities, please visit Amazon Q Developer FAQs page.
- Pricing — Amazon Q Developer now offers two pricing tiers – Free (free), and Pro, at $19/month/user.
- Free self-paced course on AWS Skill Builder — Amazon Q Introduction is a 15-minute course that provides a high-level overview of Amazon Q, a generative AI–powered assistant, and the use cases and benefits of using it. This course is part of Amazon’s AI Ready initiative to provide free AI skills training to 2 million people globally by 2025.
Visit our Amazon Q Developer Center to find deep-dive technical content and to discover how you can speed up your software development work.
Happy building,
— Donnie
from AWS News Blog https://ift.tt/37stzVU
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